Title :
Research on public opinion based on Big Data
Author :
Songtao Shang ; Minyong Shi ; Wenqian Shang ; Zhiguo Hong
Author_Institution :
Sch. of Comput. Sci., Commun. Univ. of China, Beijing, China
fDate :
June 28 2015-July 1 2015
Abstract :
Public opinion is the people´s response for social phenomena, issues, hot topics, attitudes, emotions, and so on. It reflects the focus problems of the current time of the society. By analyzing the public opinion, we can infer what will happen in the next time, and give better decision support for governments and businesses. Big Data technology is becoming a powerful data analyzing tools for massive data in recent years. Hadoop is an open source massive data processing platform based on Big Data. Mahout is a data mining algorithms´ set based on Hadoop, which is designed for processing large-scale and complex data. In most instances, the public opinion information contains many text messages. For many traditional text mining algorithms, it is almost impossible to handle high dimensional data concerns large-volume and complex data sets. Hence, this paper uses Mahout text mining algorithms to process public opinion information.
Keywords :
Big Data; Internet; data analysis; data mining; text analysis; Big Data technology; Hadoop; Mahout text mining algorithms; data analyzing tools; data mining algorithm; open source massive data processing platform; public opinion; Algorithm design and analysis; Big data; Classification algorithms; Clustering algorithms; Data mining; Internet; Machine learning algorithms; Big Data; Hadoop; Mahout; data mining; public opinion;
Conference_Titel :
Computer and Information Science (ICIS), 2015 IEEE/ACIS 14th International Conference on
Conference_Location :
Las Vegas, NV
DOI :
10.1109/ICIS.2015.7166655